• Title/Summary/Keyword: Technology standard model

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Evaluation of the Impact of Fuel Economy by Each of Driving Modes for Medium-Size Low-Floor Bus (중형저상버스의 개별주행모드에 따른 연료소비율 평가)

  • Jung, Jae-wook;Ro, Yun-sik;Ahn, Byong-kyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.9
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    • pp.133-140
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    • 2016
  • The Ministry of Land, Infrastructure and Transport has introduced low-floor buses, which are convenient for passengers getting on and off the bus and for the handicapped. The standard bus model is 11 m long and uses compressed natural gas (CNG). However, this model has drawbacks in narrow rural road conditions such as those in farming and fishing villages and mountainous areas, as well as difficulty in refueling since CNG facilities are not readily available. In this study, running resistance values were obtained by coasting performance tests on actual roads using a Tata Daewoo LF-40 model with three different weight conditions: curb vehicle weight (CVW), half vehicle weight (HVW), and gross vehicle weight (GVW).The test methods include WHVC, NIER-06, and constant-speed driving at 60 km/h. These tests were used to measure the fuel economy of vehicles other than the target vehicles to obtain the combined fuel economy. The energy efficiency was highest in the case of CVW. In the WHVC mode, the fuel consumption rates of HVW and GVW were typically 3.5% and 12% higher than that of CVW, respectively. In constant-speed driving, the fuel efficiency of HVW was higher than that of CVW. Further research is required to analyze the exhaust gas data.

Experimental Evaluation of the Effect of Fine Contents on the Formation of Underground Cavities and Ground Cave-ins by Damaged Sewer Pipes (하수관 손상으로 인한 지하공동 및 지반함몰 발생에 대해 세립분 함량이 미치는 영향의 실험적 평가)

  • Kwak, Tae-Young;Lee, Seung-Hwan;Chung, Choong-Ki;Baek, Sung-Ha
    • Journal of the Korean Geotechnical Society
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    • v.37 no.11
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    • pp.93-105
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    • 2021
  • In this study, we evaluated the effect of soil fine contents on the formation of underground cavities and ground cave-ins induced by damaged sewer pipes. Simulating the domestic rainfall conditions and ground conditions, model tests were performed under three different fine particle contents conditions (7.5%, 15%, and 25%). By repeating the groundwater supply and drainage twice, ground settlement and the amount of discharged soil were obtained. Also, digital images were taken at regular time intervals during the model tests, and internal displacement and deformation were measured using PIV technique. As the cycles were repeated, the soil with high fine content showed greater resistance to the formation of underground cavities. The ground cave-ins, identified by the collapse of the surface, occurred only when the fine particle content was 15%. It is presumed to be due to the suffusion phenomenon; further study was needed to investigate the effect of fine particle contents on the suffusion phenomenon and associated changes of soil strength.

Parameter Estimates for Genetic Effects on Growth Traits of Korean Native Goats (한국재래산양의 발육형질에 대한 유전능력 평가)

  • Kim, Y.K.;Lee, J.W.;Choi, S.H.;Son, S.G.;Na, G.J.;Moon, S.J.;Kim, J.H.
    • Journal of Animal Science and Technology
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    • v.44 no.2
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    • pp.171-180
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    • 2002
  • Data were collected from 1996 through 2000 on Korean Native Goats by the National Livestock Research Institute of Korea were used to estimate genetic parameters for birth, 3 month, and 6 month body weights. Estimates were obtained with MTDFREML. Model included animal and maternal genetic and residual effects. The model included sex, birth year-season, and feeding type as fixed factors. Average body weights and standard deviation were 1.78${\pm}$0.32 at birth of age, 7.99${\pm}$2.66 at 3 month of age, and 12.08${\pm}$3.20 kg at 6 month of age, respectively. Average body measurements were 36.46cm for withers height, 38.06cm for body length, and 45.56cm for heart girth at 3 month of age, and were 40.27cm for withers height, 42.01cm for body length, and 51.07cm for heart girth at 6 month of age, respectively. Estimates of heritability were 0.66 for birth weight, 0.34 for 3 month body weight, and 0.27 for 6 month body weight, respectively. Maternal effects would be important for birth and 3 month body weights and may not be needed in a model for 6 month body weight.

Automated Construction Progress Management Using Computer Vision-based CNN Model and BIM (이미지 기반 기계 학습과 BIM을 활용한 자동화된 시공 진도 관리 - 합성곱 신경망 모델(CNN)과 실내측위기술, 4D BIM을 기반으로 -)

  • Rho, Juhee;Park, Moonseo;Lee, Hyun-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.21 no.5
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    • pp.11-19
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    • 2020
  • A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.

Impact of the COVID-19 Pandemic on Nursing Students' Adjustment to College Life : Focus on empathic ability, perceived stress, and resilience (코로나19 팬데믹이 간호대학생의 대학생활적응에 미치는 영향 : 공감능력, 지각된 스트레스, 회복탄력성을 중심으로)

  • Yooun-Sook Choi;Mi-Young Kim
    • Journal of The Korean Society of Integrative Medicine
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    • v.12 no.1
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    • pp.97-108
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    • 2024
  • Purpose : In this study, we aimed to determine the impact of the COVID-19 pandemic on nursing students' adjustment to college life by focusing on their empathic ability, perceived stress, and resilience. Methods : We applied a descriptive survey research design, which included a self-report questionnaire. The participants comprised 307 nursing students in B city. The data were analyzed by calculating the percentages, means, standard deviations, t-tests, ANOVA, Scheffé test, Pearson's correlation coefficients, and hierarchical regression using SPSS 23.0. Results : The participants' empathic ability score was 3.30±.42, perceived stress score 1.85±.49, resilience score 3.44±.64, and adjustment to college life score 3.25±.52. Adjustment to college life was positively correlated with resilience (r=.43, p<.001) but negatively correlated with perceived stress (r=.27, p<.001). Factors affecting adjustment to college life include, among general characteristics in Model 1, in descending order, major satisfaction-satisfied (β=.54, p<.001), interpersonal conflict: never (β=.26, p=.018), health status: healthy (β=.25, p=.002), character: positive (β=.21, p=.006), character: optimistic (β=.19, p=.015), parents' economic power: high (β=.15, p=.047), and gender: male (β=.11, p=.016). Model 1 was statistically significant (F=11.67, p<.001), and the explanatory power was 41 %. In Model 2, empathic ability, perceived stress, and resilience were added as independent variables. When including the dependent variables, the factors that most influenced adjustment to college life were perceived stress (β=-.37, p<.001), major satisfaction-satisfied (β=.36, p<.001), health status-healthy (β=.25, p<.001), gender-male (β=.10, p=.015), and resilience (β=.10, p=.029). Model 2 was statistically significant (F=17.65, p<.001), and the explanatory power was 56 %. Conclusion : We found that gender, major satisfaction, health status, perceived stress, and resilience affected adjustment to college life among nursing students who had experienced the COVID-19 pandemic. To increase their ability to adjust to college life, a gender-specific intervention program should be developed that can improve the students' health status, major satisfaction and resilience, and reduce their perceived stress.

Analysis of Parameters Effecting MOBILE WiMAX Connectivity (모바일 WiMAX의 연결성 매개변수 효율 분석)

  • Chowdhury, Olly Roy;Kaiser, Arif;Kabir, Ekramul;Aditya, Subrata Kumar;Park, Jang-Woo
    • Journal of Advanced Navigation Technology
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    • v.18 no.1
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    • pp.84-89
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    • 2014
  • Worldwide Interoperability for Microwave Access (WiMAX) is an efficient technology for 20th century communication system. The technology provides broadband speed without the need for cables and is based on the IEEE 802.16 standard(also called Wireless MAN). Mobile WiMAX is defined as IEEE802.16e which is advanced and efficient technology for mobile telecommunication rather than GSM, CDMA technology. In this work link budget calculation for WiMAX have been done. Cell range have been calculated over digital modulations and they are BPSK, QPSK and QAM. Here different types of models like Cost 231 model have been used for different types of areas like open, rural and urban areas and Erceg-Greenstein model for sub-urban areas. Effect of various parameters like frequency, base station antenna height, transmission power and SNR over cell range have been studied. Analysis have done for both uplink and downlink.

lp-norm regularization for impact force identification from highly incomplete measurements

  • Yanan Wang;Baijie Qiao;Jinxin Liu;Junjiang Liu;Xuefeng Chen
    • Smart Structures and Systems
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    • v.34 no.2
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    • pp.97-116
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    • 2024
  • The standard l1-norm regularization is recently introduced for impact force identification, but generally underestimates the peak force. Compared to l1-norm regularization, lp-norm (0 ≤ p < 1) regularization, with a nonconvex penalty function, has some promising properties such as enforcing sparsity. In the framework of sparse regularization, if the desired solution is sparse in the time domain or other domains, the under-determined problem with fewer measurements than candidate excitations may obtain the unique solution, i.e., the sparsest solution. Considering the joint sparse structure of impact force in temporal and spatial domains, we propose a general lp-norm (0 ≤ p < 1) regularization methodology for simultaneous identification of the impact location and force time-history from highly incomplete measurements. Firstly, a nonconvex optimization model based on lp-norm penalty is developed for regularizing the highly under-determined problem of impact force identification. Secondly, an iteratively reweighed l1-norm algorithm is introduced to solve such an under-determined and unconditioned regularization model through transforming it into a series of l1-norm regularization problems. Finally, numerical simulation and experimental validation including single-source and two-source cases of impact force identification are conducted on plate structures to evaluate the performance of lp-norm (0 ≤ p < 1) regularization. Both numerical and experimental results demonstrate that the proposed lp-norm regularization method, merely using a single accelerometer, can locate the actual impacts from nine fixed candidate sources and simultaneously reconstruct the impact force time-history; compared to the state-of-the-art l1-norm regularization, lp-norm (0 ≤ p < 1) regularization procures sufficiently sparse and more accurate estimates; although the peak relative error of the identified impact force using lp-norm regularization has a decreasing tendency as p is approaching 0, the results of lp-norm regularization with 0 ≤ p ≤ 1/2 have no significant differences.

Deformation of the Reference Korean Voxel Model and Its Effect on Dose Calculation (표준한국인 체적소 모델 HDRK-Man의 외형 보정 및 선량 산출에 미치는 영향 평가)

  • Jeong, Jong-Hwi;Cho, Sung-Koo;Cho, Kun-Woo;Kim, Chan-Hyeong
    • Journal of Radiation Protection and Research
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    • v.33 no.4
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    • pp.167-172
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    • 2008
  • Recently a high-quality voxel model of a Korean adult male was constructed at Hanyang University by using very high resolution serially-sectioned anatomical images of a cadaver, which was provided by the Korean Institute of Science and Technology Information (KISTI). Most existing voxel phantoms are developed based on an individual in the supine posture. This study converted the HDRK-Man voxel model into surface model and adjusted the flattened back of the HDRK-Man to a normal shape in the upright posture using 3D graphic softwares such as $3D-DOCTOR^{TM}$, $Rapidform^{(R)}$2006, $Rhinoceros^{(R)}$4.0, $MAYA^{(R)}$8.5. The effective doses of adjusted model were compared with those of unadjusted model for some standard irradiation geometries (i.e., AP, PA, LLAT, RLAT). In general, the differences were not very large and, among those, the largest difference was found for the PA radiation geometry, as expected. These methodologies can be used for the development of various deformed posture models of HDRK-Man in the later stage of this project.

A Decision Support Model for Optimal Delivery of Public Construction Projects (공공건설사업의 최적 발주방식 선정을 위한 의사결정지원모델)

  • Park, Heetaek;Park, Chansik
    • Korean Journal of Construction Engineering and Management
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    • v.17 no.5
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    • pp.22-34
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    • 2016
  • The Project Delivery System (PDS) is used in mixed way without clear classification from tendering system and the standard itself that can be selected is set with project budget or estimated cost only. Essentially, the PDS should consider and reflect project characteristics and types, internal and external factors for the purpose of improving the lives of citizens and their welfare. However, the current status is not operated flexibly due to the given budget, period and uniform laws and regulations. In order to solve this problem, this study suggests a Decision Support Model to select the optimal PDS for public construction projects. The current problem of the PDS for public construction projects were identified and the application of a decision support model was proposed. Subsequently a decision-making model was suggested for each PDS using the identified factors and linear discriminant function of discriminant analysis. An additional questionnaire survey and actual practical case analysis were carried out to verify the effectiveness and applicability of the model to actual work. It can be used by adjusting the decision support model and detailed factors according to the specific characteristics of public organization, ability of person in charge and project type.

A Study of the Nonlinear Characteristics Improvement for a Electronic Scale using Multiple Regression Analysis (다항식 회귀분석을 이용한 전자저울의 비선형 특성 개선 연구)

  • Chae, Gyoo-Soo
    • Journal of Convergence for Information Technology
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    • v.9 no.6
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    • pp.1-6
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    • 2019
  • In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.